The rapid advancements in omics technologies, including proteomics, genomics, and transcriptomics, have revolutionized the field of metabolic engineering by offering unprecedented insights into cellular mechanisms and metabolic pathways. Synthetic biology tools, when integrated with these omics approaches, enable the rational design and optimization of microbial and plant systems for the efficient production of value-added products such as biofuels, pharmaceuticals, and specialty chemicals. Genomics provides a comprehensive understanding of the genetic architecture, while transcriptomics reveals dynamic changes in gene expression in response to environmental stimuli or genetic modifications. Proteomics, in turn, offers a detailed view of the functional protein landscape, enabling the identification of bottlenecks and the fine-tuning of metabolic pathways. This chapter highlights the synergistic application of these omics platforms to enhance synthetic biology projects, emphasizing case studies of successful metabolic engineering endeavors. Furthermore, it discusses cutting-edge tools, including CRISPR-Cas systems, computational modelling, and machine learning, which are reshaping the design-build-test-learn (DBTL) cycle in synthetic biology. Challenges such as data integration, system complexity, and scalability are also addressed, along with potential solutions. By exploring the interplay between omics technologies and synthetic biology, this chapter underscores the transformative potential of a systems biology approach in overcoming metabolic engineering bottlenecks, paving the way for sustainable and economically viable biotechnological solutions.